早产儿视网膜病变的危险因素分析及Nomogram预测模型的构建  

Analysis of Risk Factors for Retinopathy of Prematurity and Construction of Its Nomogram Model

作　　者：蒋韵红 路玲[2] 郭立珍 崔凤静[2] 刘冬云[2] 

机构地区：[1]青岛大学医学部,山东 青岛 [2]青岛大学附属医院儿童医学中心,山东 青岛

出　　处：《临床医学进展》2023年第7期11836-11846,共11页Advances in Clinical Medicine

摘　　要：目的:早产儿视网膜病变(ROP)是一种早产儿较常见的视网膜神经血管性疾病,可导致儿童视力缺陷甚至失明。本研究的目的是利用产妇和新生儿的临床参数建立早产儿ROP的预测模型,为ROP早期干预提供临床依据。方法:该单中心回顾性研究共纳入309例早产儿,收集人口统计学及临床资料。应用LASSO回归分析筛选变量,多变量logistic回归分析构建nomogram模型。通过计算曲线下面积(AUC)来确定模型的判别能力,Hosmer-Lemeshow检验校正模型,决策曲线分析(DCA)评估模型的临床效益性。结果:通过LASSO分析确定的预测因素为输血≥3次、吸氧≥2周、FiO2 ≥ 0.3使用24 h以上、出生胎龄、出生体重和生后体重增加率。训练集(n = 216)建立的nomogram预测模型的AUC为0.859,HL P = 0.3803;在内部验证(n = 93)中,AUC为0.853,模型具有理想的鉴别和校正效果。结论:基于以上六项参数建立的nomogram模型对早产儿ROP发生的预测具有重要价值。Objective: Retinopathy of prematurity (ROP) is a common neurovascular disease of the retina in preterm infants that can lead to visual defects and even blindness in children. The purpose of this study is to develop a predictive model for ROP in preterm infants using maternal and neonatal clin-ical parameters to provide a clinical basis for early intervention in ROP. Methods: 309 preterm in-fants were included in this single-center retrospective study, and demographic and clinical data were collected. LASSO regression analysis was applied to screen the variables, and multivariate lo-gistic regression analysis was used to construct the nomogram model. The discriminative power of the model was determined by calculating the area under the curve (AUC), the Hosmer-Leme- show test was used to correct the model, and decision curve analysis (DCA) was used to assess the clinical effectiveness of the model. Results: Predictors identified by LASSO analysis were transfusion ≥3 times, oxygen ≥2 weeks, FiO2 ≥ 0.3 used for more than 24 h, gestational age at birth, birth weight, and rate of postnatal weight gain. The AUC of the nomogram prediction model established in the training set (n = 216) was 0.859 with HL P = 0.3803;in the internal validation (n = 93), the AUC was 0.853 and the model had ideal discrimination and correction. Conclusions: The nomogram model based on the above six parameters is of great value in predicting the occurrence of ROP in preterm infants.

关 键 词：ROP 早产儿 危险因素 Nomogram模型 

分 类 号：R72[医药卫生—儿科]